This project examines the impact of education on a woman's life cycle fertility plans through its effects on age at marriage and marital fertility control . It will explore how the availability of educational resources and the actual educational attainment of a woman influence her decisions to have children through their impacts on her age at marriage and on her ability and desire to modify her contraceptive efforts in response to births and deaths in the family. The project develops a life cycle stochastic optimization model that permits a wide range of important interactions, and it explores methods for uncovering meaningful economic and behavioral relationships that require fewer assumptions than most existing applications of dynamic optimization models. It proposes a detailed statistical model of life course events that (1) follows directly from the implicit structure of the theoretical model and (2) incorporates explicitly many of the biological determinants of fertility. The theoretical model also suggests important sources of endogeneity for many of the determinants of behavior over time, and the study devises methods to control for such potential biases based upon discrete factor approximations for the unobservable variables giving rise to statistical endogeneity. These models incorporate the possible endogeneity of the education and age at marriage decisions with the life cycle marital fertility model developed by Mroz and Weir (1990). The models show much promise for uncovering an accurate assessment of the role of education on the demand for children. Three populations undergoing fertility transitions provide the data for this analysis: rural France around the time of the fertility transition (INED), and modern Tunisia (DHS) and Zimbabwe (DHS). Excellent measures of time varying contextual and background variables can be constructed for each of these populations. These additional measures permit a detailed sensitivity analysis of the empirical significance of controlling for the potential endogeneities when estimating the impacts of education and age at marriage on life cycle fertility.